Pituitary adenoma associated with xanthogranuloma.

Xanthogranuloma (XG) of the sellar region is a non-neoplastic inflammatory lesion characterized histologically by recent and remote hemorrhage, necrotic debris, fibrosis, chronic inflammation, and cholesterol clefts with associated foreign-body giant cells. The inflammatory lesion was recognized by the World Health Organization in 2000. XG of the sellar region is rare. Cases of pituitary adenoma (PA) with an associated XG (PA/XG) are extremely rare, with a total of 16 cases in the literature. PA/XG lacks specific clinical and radiologic signs, making pre-operative diagnosis challenging. Herein, we report a case of PA/XG, describe the radiologic and pathologic findings, and discuss the role of so-called silent or "subclinical pituitary apoplexy" in the possible histogenesis of PA/XGs.

Qualitative and quantitative methods in post-chemoradiation PET for head and neck cancer.

OBJECTIVE: The aim of this study was to determine whether quantitative methods could aid in the evaluation of post-treatment head and neck scans, particularly taking human papillomavirus status into account. METHODS: Clinical readings of positron emission tomography/computed tomography scans as well as standardized uptake value (SUV)max (and other metrics) of nodes visible on PET conducted on a total of 172 patients with head and neck squamous cell cancer were examined. Locoregional recurrence at 2 years was assessed. In total 88 of these patients had close enough follow-up to determine whether individual nodes were positive or negative, and 233 nodes on these patients were compared to surgical pathology notes or follow-up (if no path was available). RESULTS: General negative predictive value (NPV) of complete response was 93% and an equivocal response was 89%; focusing on nodal recurrence, NPV was found to be 97% and positive predictive value (PPV) 46% if equivocal reads were treated as negative and NPV 98% and PPV 16% if equivocal reads were treated as positive. Using SUVmax of the hottest node with a cutoff of 3.4 gave NPV 97% and PPV 26%; a direct re-read (using 2 observers) gave NPV 98% and PPV 32% if equivocal reads were treated as negative, and NPV 99% and PPV 18% if equivocal reads were treated as positive. Using other first-order radiomics data such as SD and skewness did not improve this. CONCLUSIONS: Quantitative data such as SUVmax does not show additional value over qualitative evaluation of response to chemoradiation in head and neck tumors.

Postoperative seizures following endoscopic third ventriculostomy and choroid plexus cauterization: a case series.

OBJECTIVE: In this study, the authors sought to investigate variables associated with postoperative seizures following endoscopic third ventriculostomy and choroid plexus cauterization (ETV/CPC) for treatment of pediatric hydrocephalus. METHODS: A retrospective analysis of 37 patients who underwent ETV/CPC for treatment of hydrocephalus at an academic medical center from September 2016 to March 2021 was conducted. Demographics, etiology of hydrocephalus, operative details, electroencephalography (EEG) data, MRI findings, need for subsequent procedures, perioperative laboratory tests, medical history, and presence of clinical postoperative seizures were collected. Postoperative seizures were defined as clinical seizures within 24 hours of surgery. Eighteen patients received levetiracetam intraoperatively as well as over the next 7 days postoperatively for seizure prophylaxis. RESULTS: Of 37 included patients, 9 (24%) developed clinical seizures within 24 hours after surgery, 5 of whom subsequently had electroclinical seizures captured on video-EEG. The clinical seizures in 4 of those 5 patients (80%) may have been associated with the hemisphere of the brain through which the endoscope was introduced. The median corrected age of the cohort was 3.4 months. The median corrected age of patients who did not develop postoperative seizures was 2.3 months compared with 0.7 months for patients who did develop postoperative seizures (p > 0.99). Postoperative seizures occurred in 43% (3/7) of prenatally repaired myelomeningocele patients versus 29% (2/7) of postnatally repaired myelomeningocele patients. Of the 18 patients who received prophylactic levetiracetam, none (0%) developed postoperative seizures compared with 9 of the 19 patients (47%) who did not receive prophylactic levetiracetam (p = 0.014). CONCLUSIONS: Postoperative seizures were recorded in 24% of the pediatric patients who underwent ETV/CPC for hydrocephalus, which is higher than previously reported rates in the literature of 5%. Since 80% of the postoperative electrographic seizures may have been associated with the hemisphere through which the endoscope was introduced, the surgical entry site may contribute to postoperative seizure development. In patients who received prophylactic perioperative levetiracetam, the postoperative seizure incidence dropped to 0% compared with 47% in those who did not receive prophylactic perioperative levetiracetam. This finding indicates that the use of prophylactic perioperative levetiracetam may be efficacious in the prevention of clinical seizures in this patient population.

Recurrent acute hemorrhagic necrotizing encephalopathy associated with RAN-binding protein-2 gene mutation in a pediatric patient.

A young male child presented with recurrent episodes of seizures and altered mental status following febrile episodes on three separate occasions between his first and third birthdays. Laboratory evaluations identified SARS-CoV-2 infection during the first episode and no infective agents or antibodies in the cerebrospinal fluid during all the episodes. Brain imaging with CT and MRI revealed bilaterally symmetric patchy hemorrhagic necrotic foci in the deep brain nuclei and medial temporal lobes, prompting suspicion for an underlying predisposition to recurrent acute hemorrhagic necrotizing encephalopathy. Gene analysis confirmed a mutation in the RAN-binding protein-2 (RANBP2) gene. The patient made good recovery following treatment with IVIG, steroids and plasmapheresis, and follow-up brain imaging showed no progression of brain lesions. Early suspicion from characteristic imaging features in appropriate clinical settings will inform timely appropriate treatment and better outcome. We therefore provided short review of imaging features of acute hemorrhagic necrotizing encephalopathy.

Fatal Pediatric COVID-19 Case With Seizures and Fulminant Cerebral Edema.

The novel coronavirus, SARS-CoV-2, can present with a wide range of neurological manifestations, in both adult and pediatric populations. We describe here the case of a previously healthy 8-year-old girl who presented with seizures, encephalopathy, and rapidly progressive, diffuse, and ultimately fatal cerebral edema in the setting of acute COVID-19 infection. CSF analysis, microbiological testing, and neuropathology yielded no evidence of infection or acute inflammation within the central nervous system. Acute fulminant cerebral edema (AFCE) is an often fatal pediatric clinical entity consisting of fever, encephalopathy, and new-onset seizures followed by rapid, diffuse, and medically-refractory cerebral edema. AFCE occurs as a rare complication of a variety of common pediatric infections and a CNS pathogen is identified in only a minority of cases, suggesting a para-infectious mechanism of edema. This report suggests that COVID-19 infection can precipitate AFCE, and highlights the need for high suspicion and early recognition thereof.

Assessment of 18F-PBR-111 in the Cuprizone Mouse Model of Multiple Sclerosis.

The study aims to assess site assessment of the performance of 18F-PBR-111 as a neuroinflammation marker in the cuprizone mouse model of multiple sclerosis (MS). 18F-PBR-111 PET imaging has not been well evaluated in multiple sclerosis applications both in preclinical and clinical research. This study will help establish the potential utility of 18F-PBR-111 PET in preclinical MS research and future animal and future human applications. 18F-PBR-111 PET/CT was conducted at 3.5 weeks (n = 7) and 5.0 weeks (n = 7) after cuprizone treatment or sham control (n = 3) in the mouse model. A subgroup of mice underwent autoradiography with cryosectioned brain tissue. T2 weighted MRI was performed to obtain the brain structural data of each mouse. 18F-PBR-111 uptake was assessed in multiple brain regions with PET and autoradiography images. The correlation between autoradiography and immunofluorescence staining of neuroinflammation (F4/80 and CD11b) was measured. Compared to control mice, significant 18F-PBR-111 uptake in the corpus callosum (p < 0.001), striatum (caudate and internal capsule, p < 0.001), and hippocampus (p < 0.05) was identified with PET images at both 3.5 weeks and 5.0 weeks, and validated with autoradiography. No significant uptake differences were detected between 3.5 weeks and 5.0 weeks assessing these regions as a whole, although there was a trend of increased uptake at 5.0 weeks compared to 3.5 weeks in the CC. High 18F-PBR-111 uptake regions correlated with microglial/macrophage locations by immunofluorescence staining with F4/80 and CD11b antibodies. 18F-PBR-111 uptake in anatomic locations correlated with activated microglia at histology in the cuprizone mouse model of MS suggests that 18F-PBR-111 has potential for in vivo evaluation of therapy response and potential for use in MS patients and animal studies.

Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge.

To better understand early brain development in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). Deep learning-based methods have achieved state-of-the-art performance; h owever, one of the major limitations is that the learning-based methods may suffer from the multi-site issue, that is, the models trained on a dataset from one site may not be applicable to the datasets acquired from other sites with different imaging protocols/scanners. To promote methodological development in the community, the iSeg-2019 challenge (http://iseg2019.web.unc.edu) provides a set of 6-month infant subjects from multiple sites with different protocols/scanners for the participating methods. T raining/validation subjects are from UNC (MAP) and testing subjects are from UNC/UMN (BCP), Stanford University, and Emory University. By the time of writing, there are 30 automatic segmentation methods participated in the iSeg-2019. In this article, 8 top-ranked methods were reviewed by detailing their pipelines/implementations, presenting experimental results, and evaluating performance across different sites in terms of whole brain, regions of interest, and gyral landmark curves. We further pointed out their limitations and possible directions for addressing the multi-site issue. We find that multi-site consistency is still an open issue. We hope that the multi-site dataset in the iSeg-2019 and this review article will attract more researchers to address the challenging and critical multi-site issue in practice.

Detectable size of melanoma metastases to brain on PET/CT.

OBJECTIVE: We aimed to determine at what size melanoma metastases become detectable by PET/CT. METHODS: We reviewed a total of 293 whole-body PET/CT studies performed on 212 patients for staging of melanoma where there was an MRI within a month of the PET/CT. MR and PET/CT were reviewed independently by separate readers. RESULTS: PET/CT revealed an overall incidental true-positive rate of 1% on a per-patient basis, consistent with other studies, with 'hot' lesions (more avid than brain parenchyma) visible at smaller sizes than 'cold' lesions. CONCLUSIONS: PET/CT can detect metastatic melanoma lesions over about 2 cm in size, with hot lesions generally visible at smaller sizes.

Understanding the Radiologist's Role in Evaluating Multiple Sclerosis: A Review of the Tip of the Iceberg.

Radiologists add value in the setting of clinically suspected multiple sclerosis (MS) predominantly through knowledge of typical and atypical imaging findings, thus aiding the neurologist in differentiating multiple disease processes with similar clinical presentations which may mimic MS. This paper is meant as a guide to deepen understanding for the radiologist, enabling them to be a helpful member of the care team for MS patients.

What Can Mimic Multiple Sclerosis?

This article discusses mimics of multiple sclerosis (MS). Excluded in this discussion are neuromyelitis optica and vasculitis, discussed in other articles in this journal. Covered entities include posterior reversible encephalopathy syndrome, reversible vasoconstriction syndrome, acute disseminated encephalomyelitis, Sussac's Syndrome, and chronic idiopathic demyelinating polyneuropathy. There are also multiple infectious entities that mimic MS including; progressive multi-focal leukoencephalopathy (PML), Toxoplasmosis, Tuberculosis, Herpes Simplex Virus, Cytomegalovirus, Varicella zoster virus, Epstein Barr virus, Cryptococcus and Human immunodeficiency virus. In addition, there are leukoencephalopathies that can present in adulthood including Adrenoleukodystrophy, Metachromatic leukodystrophy, Cerebral autosomal dominant idiopathic leukoencephalopathy, Leigh's and Alexanders disease that could be mistaken for MS.

CNS Vasculitis-An Overview of This Multiple Sclerosis Mimic: Clinical and MRI Implications.

This article discusses central nervous system vasculitis, a clinical and MRI mimic of multiple sclerosis (MS). There is a paucity of discussion of vasculitis in the radiology literature, and many MS neurologists believe that vasculitis is underdiagnosed. Therefore, the authors hope that the readers will find this paper increases their knowledge about CNS vasculitis and improves their ability to differentiate MS from vasculitis.

Multimodal Image Analysis for Assessing Multiple Sclerosis and Future Prospects Powered by Artificial Intelligence.

The purpose of this paper is to serve as a template for greater understanding for the practicing radiologist about key steps to perform multimodality computer analysis of MRI images, specifically in multiple sclerosis patients. With this understanding, radiologists will be better equipped about how best to process and analyze MRI imaging data and obtain accurate quantitative information for MS patient evaluation. A secondary intent of this article is to improve radiologist understanding of how artificial intelligence will be employed in the future for better patient stratification, and for evaluation of response to therapy in both clinical care and drug trials.

Complete remission with ibrutinib after allogeneic stem cell transplant for central nervous system relapse of mantle cell lymphoma: A case report and literature review.

Central nervous system (CNS)-relapsed mantle cell lymphoma (MCL) is a rare, aggressive non-Hodgkin lymphoma without a standard treatment. Ibrutinib has shown promising results for inducing remission in other non-Hodgkin lymphomas and may be considered as successful treatment for CNS-relapsed MCL in the future as well.

Subsequent experience in hybrid PET-MRI for evaluation of refractory focal onset epilepsy.

PURPOSE: Epilepsy surgery is the most successful method of treating medically unresponsive epilepsy, but carries a risk of morbidity. PET/MR is an emerging technique that increases detection of focal lesions whose resection may result in symptom remission. METHODS: Retrospective review of 74 focal epilepsy patients over a period of 3 years who had a PET/MR was performed following IRB permission and informed consent. 27 patients underwent surgery or RNS (responsive neurostimulator) placement. RESULTS: Hybrid PET-MR identified new anatomic or functional lesions in 10 patients not identified with standalone 3 T MR. Of the 27 patients who underwent focal surgery (19) or RNS placement (8), 24 showed improvement (Engel's I-III), 2 did not (Engel's IV), and one had an RNS explanted due to infection. MR and PET were read by 2 separate neuroradiologists and nuclear medicine physicians, respectively. Modalities were evaluated in terms of ability to detect the correct lobe and side for a focal lesion whose resection improved symptoms. Prior standalone MR exhibited 71-77% sensitivity and 0% specificity (as there were only 2 nonresponders), MR associated with PET/MR had 68-71% sensitivity and 0-50% specificity (depending on whether a lesion was seen on one of the nonresponders), and PET had 68-71% sensitivity and 25-33% specificity. Using either PET or MR to identify a focal lesion, PET/MR had sensitivity of 78-82% and specificity 0-50%. CONCLUSIONS: PET-MR provides additional sensitivity when used as two combined modalities for detecting possible epileptic foci.

IL-11 antagonist suppresses Th17 cell-mediated neuroinflammation and demyelination in a mouse model of relapsing-remitting multiple sclerosis.

IL-11 induced differentiation and expansion of Th17 cells in patients with early relapsing-remitting multiple sclerosis (RRMS). In mice with relapsing-remitting experimental autoimmune encephalomyelitis (RREAE), IL-11 exacerbated disease, induced demyelination in the central nervous system (CNS), increased the percentage of IL-17A+CD4+ Th17 cells in the CNS in the early acute phase, and up-regulated serum IL-17A levels and the percentage of IL-17A+CD4+ Th17 cells in lymph nodes, and IFN-γ+CD4+ T cells in spinal cord in the RR phase. IL-11 antagonist suppressed RREAE disease activities, inhibited IL-17A+CD4+ cell infiltration and demyelination in the CNS, and decreased the percentage of IL-17A+CD4+ T cells in peripheral blood mononuclear cells and ICAM1+CD4+ T cells in brain and SC. Diffusion Tensor Imaging indicated that IL-11 antagonist inhibited demyelination in several brain regions. We conclude that by suppressing Th17 cell-mediated neuroinflammation and demyelination, IL-11 antagonist can be further studied as a potential selective and early therapy for RRMS.

Segmenting hippocampal subfields from 3T MRI with multi-modality images.

Hippocampal subfields play important roles in many brain activities. However, due to the small structural size, low signal contrast, and insufficient image resolution of 3T MR, automatic hippocampal subfields segmentation is less explored. In this paper, we propose an automatic learning-based hippocampal subfields segmentation method using 3T multi-modality MR images, including structural MRI (T1, T2) and resting state fMRI (rs-fMRI). The appearance features and relationship features are both extracted to capture the appearance patterns in structural MR images and also the connectivity patterns in rs-fMRI, respectively. In the training stage, these extracted features are adopted to train a structured random forest classifier, which is further iteratively refined in an auto-context model by adopting the context features and the updated relationship features. In the testing stage, the extracted features are fed into the trained classifiers to predict the segmentation for each hippocampal subfield, and the predicted segmentation is iteratively refined by the trained auto-context model. To our best knowledge, this is the first work that addresses the challenging automatic hippocampal subfields segmentation using relationship features from rs-fMRI, which is designed to capture the connectivity patterns of different hippocampal subfields. The proposed method is validated on two datasets and the segmentation results are quantitatively compared with manual labels using the leave-one-out strategy, which shows the effectiveness of our method. From experiments, we find a) multi-modality features can significantly increase subfields segmentation performance compared to those only using one modality; b) automatic segmentation results using 3T multi-modality MR images could be partially comparable to those using 7T T1 MRI.

Interactive and additive influences of Gender, BMI and Apolipoprotein 4 on cognition in children chronically exposed to high concentrations of PM2.5 and ozone. APOE 4 females are at highest risk in Mexico City.

Children's air pollution exposures are associated with systemic and brain inflammation and the early hallmarks of Alzheimer's disease (AD). The Apolipoprotein E (APOE) 4 allele is the most prevalent genetic risk for AD, with higher risk for women. We assessed whether gender, BMI, APOE and metabolic variables in healthy children with high exposures to ozone and fine particulate matter (PM2.5) influence cognition. The Wechsler Intelligence Scale for Children (WISC-R) was administered to 105 Mexico City children (12.32±5.4 years, 69 APOE 3/3 and 36 APOE 3/4). APOE 4v 3 children showed decrements on attention and short-term memory subscales, and below-average scores in Verbal, Performance and Full Scale IQ. APOE 4 females had higher BMI and females with normal BMI between 75-94% percentiles had the highest deficits in Total IQ, Performance IQ, Digit Span, Picture Arrangement, Block Design and Object Assembly. Fasting glucose was significantly higher in APOE 4 children p=0.006, while Gender was the main variable accounting for the difference in insulin, HOMA-IR and leptin (p<.05). Gender, BMI and APOE influence children's cognitive responses to air pollution and glucose is likely a key player. APOE 4 heterozygous females with >75% to <94% BMI percentiles are at the highest risk of severe cognitive deficits (1.5-2SD from average IQ). Young female results highlight the urgent need for gender-targeted health programmes to improve cognitive responses. Multidisciplinary intervention strategies could provide paths for prevention or amelioration of female air pollution targeted cognitive deficits and possible long-term AD progression.

Automatic Hippocampal Subfield Segmentation from 3T Multi-modality Images.

Hippocampal subfields play important and divergent roles in both memory formation and early diagnosis of many neurological diseases, but automatic subfield segmentation is less explored due to its small size and poor image contrast. In this paper, we propose an automatic learning-based hippocampal subfields segmentation framework using multi-modality 3TMR images, including T1 MRI and resting-state fMRI (rs-fMRI). To do this, we first acquire both 3T and 7T T1 MRIs for each training subject, and then the 7T T1 MRI are linearly registered onto the 3T T1 MRI. Six hippocampal subfields are manually labeled on the aligned 7T T1 MRI, which has the 7T image contrast but sits in the 3T T1 space. Next, corresponding appearance and relationship features from both 3T T1 MRI and rs-fMRI are extracted to train a structured random forest as a multi-label classifier to conduct the segmentation. Finally, the subfield segmentation is further refined iteratively by additional context features and updated relationship features. To our knowledge, this is the first work that addresses the challenging automatic hippocampal subfields segmentation using 3T routine T1 MRI and rs-fMRI. The quantitative comparison between our results and manual ground truth demonstrates the effectiveness of our method. Besides, we also find that (a) multi-modality features significantly improved subfield segmentation performance due to the complementary information among modalities; (b) automatic segmentation results using 3T multimodality images are partially comparable to those on 7T T1 MRI.